Risk Management & Real Options VIII. The Value of Flexibility Stefan Scholtes Judge Institute of...
-
date post
15-Jan-2016 -
Category
Documents
-
view
218 -
download
1
Transcript of Risk Management & Real Options VIII. The Value of Flexibility Stefan Scholtes Judge Institute of...
Risk Management & Real Options
VIII. The Value of Flexibility
Stefan ScholtesJudge Institute of Management
University of Cambridge
MPhil Course 2004-05
2 September 2004 © Scholtes 2004 Page 2
Course content
I. IntroductionII. The forecast is always wrong
I. The industry valuation standard: Net Present Value
II. Sensitivity analysisIII. The system value is a shape
I. Value profiles and value-at-risk charts
II. SKILL: Using a shape calculatorIII. CASE: Overbooking at EasyBeds
IV. Developing valuation modelsI. Easybeds revisited
V. Designing a system means sculpting its value shapeI. CASE: Designing a Parking Garage
III. The flaw of averages: Effects of
system constraintsVI. Coping with uncertainty I:
DiversificationI. The central limit theoremII. The effect of statistical
dependenceIII. Optimising a portfolio
VII. Coping with uncertainty II: The value of information
I. SKILL: Decision Tree Analysis
II. CASE: Market Research at E-Phone
VIII. Coping with uncertainty III: The value of flexibility
I. Investors vs. CEOs
II. CASE: Designing a Parking Garage II
2 September 2004 © Scholtes 2004 Page 3
Project design
Designing a project means sculpting its risk profile
Histogram
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
-£22
0,00
0,00
0
-£19
0,00
0,00
0
-£16
0,00
0,00
0
-£13
0,00
0,00
0
-£10
0,00
0,00
0
-£70
,000
,000
-£40
,000
,000
-£10
,000
,000
£10,
000,
000
£40,
000,
000
£70,
000,
000
£100
,000
,000
£130
,000
,000
£160
,000
,000
£190
,000
,000
£220
,000
,000
£250
,000
,000
£280
,000
,000
£310
,000
,000
£330
,000
,000
£360
,000
,000
£390
,000
,000
£420
,000
,000
£450
,000
,000
£480
,000
,000
Values
Fre
qu
ency
Design 1
Design 2
Value-at-risk chart
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
-200,000,000 -100,000,000 0 100,000,000 200,000,000 300,000,000 400,000,000
Target value
Pro
bab
ilit
y th
at r
eali
sed
val
ue
is l
ess
than
tar
get
val
ue
Design 1
Design 2
2 September 2004 © Scholtes 2004 Page 4
Design parameters
Where?
When?
How big?
With whom?
Etc.
2 September 2004 © Scholtes 2004 Page 5
Timing
A key issue is the timing / phasing of investments• When is the right time for which decision?
What is a decision in the first place?
A DECISION IS A COMMITMENT OF RESOURCES
NPV analysis leads us into one-off thinking• Take one decision (invest, yes/no), then the project evolves on a
fixed plan
NPV does not capture value of staging the investment• Many decisions enable you to make further decisions downstream• Commit money to “buy an option” vs. “buy cash flows”
Option: “Right but not obligation to an action in the future”
2 September 2004 © Scholtes 2004 Page 6
Pros and cons of waiting
Waiting with a decision allows you to learn / gain information• Reduce risk
Waiting can lead to loss of revenues during waiting period
Waiting can lead to loss of competitive advantage• First mover advantage, pre-emption
Need to trade-off “costs of waiting” against “value of waiting”• No obvious solution• Needs case-by-case analysis
2 September 2004 © Scholtes 2004 Page 7
Options
Postponing a decision is about keeping your option open
An option is a “right but not an obligation to a certain future action”
R&D activity buys you the option to launch a product in the future
• if and when R&D is successful and the market is right• VC portfolios are portfolios of options
Foreign direct investment offers you the opportunity to learn about the foreign market and invest in the future in a big way, if and when you believe the time and circumstances are right
2 September 2004 © Scholtes 2004 Page 8
Examples of option values
Typical pattern: • Price of option is low relative to the possible gain• If you buy an option you should realise that there is a good chance
that you never exercise it An option is a gamble
“Compound option”: Series of increasingly more expensive stages, followed by a big “final” decision
• VC investment rounds, followed by IPO• Phases of drug R&D• Exploration in oil and gas
Similar to “value of information”• Additional information has only value if you have the option to act
in the future in the light of this information
2 September 2004 © Scholtes 2004 Page 9
Options “on” systems vs. options “in” systems
Options ON systems: • Invest a relatively small amount of money for the possibility to
invest a large amount later• Example: R&D is an option to invest in launch, venture capital
investments
Options IN systems:• You are already committed to a large expenditure and can now
improve its risk and opportunity profile by adding design features• Many design features can be seen as options, i.e., giving you the
right but not the obligation to use them in the future• Examples: Y-junction in an underwater pipeline, extra strong
footings for parking garage expansion, etc.
2 September 2004 © Scholtes 2004 Page 10
Diversification vs. Flexibility
Three main risk management approaches• Diversify: passive risk / opportunity management• Remain flexible: active risk / opportunity management
Diversification is important if you don’t have control over the fate of your investment
• Owner of a fleet of ships, investor in shares• Dealt with in finance class
Flexibility is important if you are in control• Captain of the ship, CEO of company
Flexibility can increase the value of each individual project and therefore the value of the portfolio of such projects
• That’s why VC’s are interested
2 September 2004 © Scholtes 2004 Page 11
Flexibility
Flexibility is more important for managers than for investors• Managers are more likely to be held responsible for the fate of one /
few big projects then for the fate of a portfolio of many investments
Flexibility is only helpful if it is used skilfully in the future• That’s why VC’s are so interested in the quality of the management
team
Flexibility is only valuable if there is uncertainty about the future
• The more uncertainty there is the better for the skilful manager• Avoid downsides, amplify upsides, beat the competition
A good captain likes a stormy sea…
2 September 2004 © Scholtes 2004 Page 12
Option value: A stylised example
You own an oil reservoir, what’s the value
What’s the value if• Volume 10 M bbl – no uncertainty• If you pump oil out, it will cost you $39/bbl – no uncertainty• Oil price projection is $40/bbl – no uncertainty
What’s the value if there are two price scenarios with 50/50 chance:
• Oil price can go up to $45 or down to $35• Does the uncertainty increase or decrease the value?
What’s the value if the uncertainty in oil prices increases?• Upside scenario $50, downside scenario $30 • Does additional uncertainty increase or decrease the value?
2 September 2004 © Scholtes 2004 Page 13
The options view of capacity
Decide on capacity of new plant
Cost of capacity: $500 / unit production capacity
Operating margin: $600 / unit sold
Projected demand 60,000 units
What’s the optimal design?
2 September 2004 © Scholtes 2004 Page 14
The options view of capacity
Decide on capacity of new plant
Cost of capacity: $500 / unit production capacity
Operating margin: $600 / unit sold
Projected demand 60,000 units
What’s the optimal design?• Gain $100 for each unit capacity up to 60,000 units• Build 60,000 units capacity• Value = 60,000*$100= $6 M
2 September 2004 © Scholtes 2004 Page 15
The options view of capacity
Decide on capacity of new plant
Cost of capacity: $500 / unit production capacity
Operating margin: $600 / unit sold
Projected demand• 40,000 units – 50%• 80,000 units – 50%
What’s the expected value of the chosen design?
2 September 2004 © Scholtes 2004 Page 16
The options view of capacity
Decide on capacity of new plant
Cost of capacity: $500 / unit production capacity
Operating margin: $600 / unit sold
Projected demand• 40,000 units – 50%• 80,000 units – 50%
What’s the expected value of the chosen design?• Upside 60,000*$100 = $6M• Downside 40,000*$100 – 20,000*$500 = -$6M• Average value = $0 Flaw of averages
2 September 2004 © Scholtes 2004 Page 17
The options view of capacity
Decide on capacity of new plant
Cost of capacity: $500 / unit production capacity
Operating margin: $600 / unit sold
Projected demand• 40,000 units – 50%• 80,000 units – 50%
Can we improve on our design?
2 September 2004 © Scholtes 2004 Page 18
The options view of capacity
Decide on capacity of new plant
Cost of capacity: $500 / unit production capacity
Operating margin: $600 / unit sold
Projected demand• 40,000 units – 50%• 80,000 units – 50%
Can we improve on our design?• Gain $100 up for each unit of capacity up to downside demand of
40,000• Loose on average for each unit of capacity above 40,000
Q̵ Expected loss per unit = 50%*$600-$500=-$200
2 September 2004 © Scholtes 2004 Page 19
The options view of capacity
Optimizing Capacity
-$4,000,000
-$2,000,000
$0
$2,000,000
$4,000,000
$6,000,000
$8,000,000
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Capacity
Exp
ecte
d V
alu
e o
f th
e S
yste
m
Single Scenario Tw o Scenarios
2 September 2004 © Scholtes 2004 Page 20
The options view of capacity
Risk Profiles of Designs
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
-$12,000,000
-$10,000,000
-$8,000,000
-$6,000,000
-$4,000,000
-$2,000,000
$0 $2,000,000
$4,000,000
$6,000,000
Realised Value
Pro
bab
ilit
y
Large
Small
Plus: Building small avoids downside riskMinus: Building small reduces upside potential
2 September 2004 © Scholtes 2004 Page 21
The options view of capacity
Smart solution: Build small but allow for later expansion
Suppose after demand scenario has been observed, 50% of excess demand can still be captured through expansion
How should we stage and what’s the value of the staged project?
2 September 2004 © Scholtes 2004 Page 22
The options view of capacity
No uncertainty after demand scenario has been observed• Build 50% of excess demand as expansion capacity
Optimizing initial capacity:
Design Optimization
0
1000000
2000000
3000000
4000000
5000000
6000000
0 10000 20000 30000 40000 50000 60000
Initial Capacity
Exp
ecte
d V
alu
e
2 September 2004 © Scholtes 2004 Page 23
The options view of capacity
Risk Profiles of Designs
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
-$12,000,000
-$10,000,000
-$8,000,000
-$6,000,000
-$4,000,000
-$2,000,000
$0 $2,000,000
$4,000,000
$6,000,000
Realised Value
Pro
bab
ilit
y
Large
Small
Two-stage
2 September 2004 © Scholtes 2004 Page 24
The options view of capacity
Expansion capability is an option on demand
Value of the option: (=) value of the best two-stage design
(-) value of the best one-stage design
(=) $5,000,000 – $4,000,000 = $1,000,000
May have to invest some of the option value in advance to “buy” the option
• Trade-off between price and value of the option
2 September 2004 © Scholtes 2004 Page 25
The options view of capacity
Options are the more valuable the more risky the environment
Uncertainty level = Distance between the two demand scenarios
System and option value as a function of uncertainty level
$0
$1,000,000
$2,000,000
$3,000,000
$4,000,000
$5,000,000
$6,000,000
$7,000,000
0% 10% 20% 30% 40% 50% 60%
Uncertainty Level = Percentage Deviation Up or Down from Projection
Value of non-staged system Value of staged system Option Value
2 September 2004 © Scholtes 2004 Page 26
Summary
Options allow you to exploit upsides and avoid suffering from downsides
Option value increases with increasing uncertainty
Options need to be thought of in the initial design phase
Trade-off cost of the option with its value
NOW TO A CASE: PARKING GARAGE, PART II